Pore network analysis is used to investigate the effects of microscopic par
ameters of the pore structure such as pore geometry, pore-size distribution
, pore space topology and fractal roughness porosity on resistivity index c
urves of strongly water-wet porous media. The pore structure is represented
by a three-dimensional network of lamellar capillary tubes with fractal ro
ughness features along their pore-walls. Oil-water drainage (conventional p
orous plate method) is simulated with a bond percolation-and-fractal roughn
ess model without trapping of wetting fluid. The resistivity index, saturat
ion exponent and capillary pressure are expressed as approximate functions
of the pore network parameters by adopting some simplifying assumptions and
using effective medium approximation, universal scaling laws of percolatio
n theory and fractal geometry. Some new phenomenological models of resistiv
ity index curves of porous media are derived. Finally, the eventual changes
of resistivity index caused by the permanent entrapment of wetting fluid i
n the pore network are also studied.
Resistivity index and saturation exponent are decreasing functions of the d
egree of correlation between pore volume and pore size as well as the width
of the pore size distribution, whereas they are independent on the mean po
re size. At low water saturations, the saturation exponent decreases or inc
reases for pore systems of low or high fractal roughness porosity respectiv
ely, and obtains finite values only when the wetting fluid is not trapped i
n the pore network. The dependence of saturation exponent on water saturati
on weakens for strong correlation between pore volume and pore size, high n
etwork connectivity, medium pore-wall roughness porosity and medium width o
f the pore size distribution. The resistivity index can be described succes
fully by generalized 3-parameter power functions of water saturation where
the parameter values are related closely with the geometrical, topological
and fractal properties of the pore structure.